U.S. patent application number 13/695880 was filed with the patent office on 2013-02-28 for system and method for evaluating a reverse query.
This patent application is currently assigned to Axiomatics AB. The applicant listed for this patent is Pablo Giambiagi, Erik Rissanen. Invention is credited to Pablo Giambiagi, Erik Rissanen.
Application Number | 20130055344 13/695880 |
Document ID | / |
Family ID | 44900240 |
Filed Date | 2013-02-28 |
United States Patent
Application |
20130055344 |
Kind Code |
A1 |
Rissanen; Erik ; et
al. |
February 28, 2013 |
SYSTEM AND METHOD FOR EVALUATING A REVERSE QUERY
Abstract
Disclosed are real-time techniques for determining all access
requests to an attribute-based access control policy which evaluate
to a given decision, "permit" or "deny". The policy is enforced to
control access to one or more resources in a computer network. In
one embodiment, a method comprises: (i) receiving a reverse query
and a set of admissible access requests, each of which comprises
one or more attributes in the policy and values of these; (ii)
extracting attributes to which all access requests in the set
assign identical values; (iii) reducing the ABAC policy by
substituting values for the extracted attributes; (iv) caching the
policy as a simplified policy; (v) translating the simplified
policy and the given decision into a satisfiable logic proposition;
(vi) deriving all solutions satisfying the proposition; and (vi)
extracting, based on the solutions, all access requests from the
set for which the policy yields the given decision.
Inventors: |
Rissanen; Erik; (Kista,
SE) ; Giambiagi; Pablo; (Stockholm, SE) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Rissanen; Erik
Giambiagi; Pablo |
Kista
Stockholm |
|
SE
SE |
|
|
Assignee: |
Axiomatics AB
Stockholm
SE
|
Family ID: |
44900240 |
Appl. No.: |
13/695880 |
Filed: |
July 19, 2011 |
PCT Filed: |
July 19, 2011 |
PCT NO: |
PCT/SE11/50955 |
371 Date: |
November 2, 2012 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
61435058 |
Jan 21, 2011 |
|
|
|
Current U.S.
Class: |
726/1 |
Current CPC
Class: |
G06F 2221/2141 20130101;
G06F 21/604 20130101 |
Class at
Publication: |
726/1 |
International
Class: |
G06F 21/00 20060101
G06F021/00 |
Foreign Application Data
Date |
Code |
Application Number |
Dec 30, 2010 |
SE |
1051394-3 |
Claims
1. A computer-implemented method for real-time evaluation of a
reverse query to an attribute-based access control (ABAC) policy
(P), which is enforced to control access to one or more resources
in a computer network, said method comprising the steps of: i)
receiving a reverse query indicating a given decision (d), which is
one of permit access and deny access, and a set (R) of admissible
access requests, each of which comprises one or more attributes
appearing in the ABAC policy and explicit values assigned to these;
ii) extracting attributes to which all access requests in the set
(R) assign identical values; iii) reducing the ABAC policy at least
by substituting values for the extracted attributes; iv) caching
the policy after said reducing as a simplified policy (P'); v)
translating the cached simplified policy (P') and the given
decision (d) into a satisfiable logic proposition in Boolean
variables (v.sub.i, i=1, 2, . . . ); vi) deriving all variable
assignments (c.sub.j=[v.sub.1=x.sub.j1, v.sub.2=x.sub.j2, . . . ],
j=1, 2, . . . ) satisfying the logic proposition; and vii)
extracting, based on the variable assignments thus derived, all
access requests from the set (R) for which the ABAC policy (P)
yields the given decision (d).
2. The method of claim 1, wherein step ii includes examining the
set (R) of access requests in order to determine: a first set (D)
of attributes that are associated with exactly the same set of
values in all requests of said subset (R); a second set (A) of
attributes that are absent in all requests of said subset (R); and
a third set (U) of all other attributes not included in any of the
sets (D or A) of attributes.
3. The method of claim 2, wherein step iii includes using said sets
(D, A, U) of attributes to generate a partial access request,
which: assigns, to each attribute in said first set (D) of
attributes, the exact set of values associated to it by any request
in said set (R); and leaves all attributes in said set (U)
undefined.
4. The method of claim 3, wherein the partial access request
further (V) marks all attributes in said set (A) as not
present.
5. The method of claim 1, wherein step iv includes caching the
simplified policy (P') represented with a tree structure, wherein
step v includes, whenever a sub-tree in the tree structure
represents a Boolean expression that compares an attribute with a
fixed value, replacing said whole sub-tree by a variable
(v.sub.i).
6. The method of claim 1, wherein step iv includes caching the
simplified policy (P') represented with a tree structure, wherein
step v includes, whenever a sub-tree in the tree structure
represents a Boolean expression but at least one of its children
evaluates to a non-Boolean value, replacing said whole sub-tree by
a variable (v.sub.i).
7. The method claim 5, wherein, in step v, the variable replacing
the sub-tree comprises two associated Boolean variables for
representing more than two possible values of the sub-tree.
8. The method of claim 7, said possible values being "true",
"false" and "indeterminate".
9. The method of claim 1, wherein step v includes storing a
correlation between each variable (v.sub.i) and the sub-tree which
it replaces.
10. The method of claim 1, wherein step vii includes assessing, for
each request (r) in the set (R) of requests, whether it corresponds
to any of the variable assignments satisfying the logic expression;
and, if it does, extracting this access request.
11. The method of claim 1, wherein step vi is performed by means of
a SAT solver.
12. The method of claim 1, wherein step v includes representing at
least part of the simplified policy (P') as a binary decision
diagram; and wherein step vi includes deriving all paths in the
binary decision diagram evaluating to either true or false.
13. The method of any of the preceding claims claim 1, wherein step
iii includes: determining an implicit reference defined by a value
of one of said extracted attributes together with the ABAC policy;
and fetching, in accordance with this implicit reference, at least
one attribute value from a remote source.
14. A computer program product comprising a data carrier storing
computer-executable instructions for performing the method of claim
1.
15. A computer system configured for real-time evaluation of a
reverse query to an attribute-based access control (ABAC) policy,
which is enforced to control access to one or more resources in a
computer network, wherein the reverse query indicates a given
decision (d), which is one of permit access and deny access, and a
set (R) of admissible access requests, each of which comprises one
or more attributes appearing in the ABAC policy and explicit values
assigned to these, said computer system comprising: a data memory
(12) operable to store one or more ABAC policies; a partial request
generation means operable to construct, based on said set (R) of
admissible access requests, a partial request (r.sub.partial)
assigning values only to attributes associated with identical
values throughout the set (R) of admissible requests; a policy
decision means connected to said partial request generation means
and to the electronic storing means, and operable to evaluate said
policy (P) for said partial request (r.sub.partial), thereby
yielding a simplified policy (P'); a translation means, connected
to said policy decision means and operable to translate said
simplified policy (P'), said subset (R) of said set of possible
requests, and said given decision (d) into a satisfiable logic
proposition (F) in Boolean variables (v.sub.i, i=1, 2, . . . ); an
analyzing means 483, connected to said translation means and
operable to analyze said propositional logic formula (F) in order
to determine a sequence ([c.sub.1, . . . , c.sub.k]) of conditions
over requests, each condition defining a variable assignment
(c.sub.j=[v.sub.1=x.sub.j1, v.sub.2=x.sub.j2, . . . ], j=1, 2, . .
. ); and a conversion means connected to said analyzing means, and
operable to extract, based on said sequence [c.sub.1, . . . ,
c.sub.k] of conditions, valid requests contained in said subset (R)
which evaluate to said given decision (d).
Description
FIELD OF THE INVENTION
[0001] The invention disclosed herein generally relates to the
field of access control (AC), particularly access control to
resources in computer systems or computer-aided access control to
other types of resources. More precisely, the invention provides
improved devices and methods for evaluating a policy for a reverse
query, which returns such access requests that evaluate to a given
decision.
BACKGROUND OF THE INVENTION
[0002] An attribute-based AC (ABAC) policy defines access control
permissions based on the attributes of the subject, of the
resource, and of the action that the subject is to perform on the
resource (e.g., read, write). When the policy is enforced in a
computer system or computer network, it controls access to entities
in the system or network and thereby influences their state of
operation. A resource may be, inter alia, a portion of a personal
storage quota, a business unit storage quota, an information
retrieval system, a (portion of a) database, an online service, a
protected webpage or a physical device.
[0003] There currently exist general-purpose AC languages that have
the richness to express fine-grained conditions and conditions
which depend on external data. One particular example of an AC
language is the eXtensible Access Control Markup Language (XACML)
which is the subject of standardization work in a Technical
Committee within the Organization for the Advancement of Structured
Information Standards (see http://www.oasis-open.org). A policy
encoded with XACML consists of functional expressions in attribute
values, and the return value (decision) of the policy is one of
Permit, Deny, Not Applicable, or Indeterminate. An XACML policy can
apply to many different situations, that is, different subjects,
resources, actions and environments and may give different results
for different combinations of these. The XACML specification
defines how a policy is evaluated for a request (or access
request), particularly what policy attributes are to be evaluated
or, at least, which values are required to exist for a successful
evaluation to result. Key characteristics of this evaluation
process are that the access request (the query against the policy)
must describe the attempted access to a protected resource fully.
In practice, it may be that the request is constructed in multiple
stages by different components, so that a PEP (Policy Enforcement
Point) provides only some initial attribute values and a PDP
(Policy Decision Point) or other components can dynamically fetch
more attribute values from remote sources as they are needed. Rules
in an ABAC policy may be nested in a conditional fashion, so that
attribute values--both those provided initially in the access
request and those fetched from remote sources--will influence what
further rules are to be applied. Based on a policy or policy set
(unless otherwise indicated, these terms are used interchangeably
herein) that covers a broad range of resources and subjects and a
given request, it is often possible to obtain a decision by
evaluating only a fraction of all functional expressions in the
policy. Conversely, it cannot always be ascertained prima facie
whether a request contains enough attribute values to allow a
successful policy evaluation.
[0004] A reverse query works in the opposite direction. It defines
an expected decision and constraints over the set of possible
access requests, and is resolved by finding the set of access
requests that (a) fulfill all the constraints, and (b) evaluate to
the expected decision. Reverse queries have many uses. For
instance, they could be used to determine the list of resources
that a subject may access, or the list of subjects that may access
a resource. Furthermore, many types of policy analyses can be built
using reverse queries (e.g., Segregation of Duty validation).
[0005] The semantics of an XACML policy P may be given as a
function f.sub.p mapping a request to a decision:
f.sub.p: Request.fwdarw.Decision
In many situations, however, it is necessary to evaluate the
inverse of the policy function,
(f.sub.p).sup.-1: Decision.fwdarw.Set(Request)
Given a decision d, (f.sub.p).sup.-1(d) is the set of all requests
that evaluate to d. For example, (f.sub.p).sup.-1 (PERMIT) is the
set of all requests that are permitted by the policy P. Note that
(f.sub.p).sup.-1 is multi-valued in general, and may be regarded as
a mapping from a decision value (Permit, Deny, etc.) to a set of
requests.
[0006] In many important applications, there is a priori a set R of
interesting requests. For instance, to determine all the users that
may "read" a certain file "F", only requests that identify the
action as "read" and the resource as "file F" are of interest. In
other words, what needs to be computed is actually the intersection
of (f.sub.p).sup.-1(d) with R,
(f.sub.p).sup.-1(d).andgate.R.
[0007] These concepts may be summarized by the following
definitions.
[0008] Definition (Reverse Query): A reverse query is a triple
<P, d, R> where P is a policy, d is a decision and R is a set
of requests.
[0009] Definition (Reverse Query Evaluation): A reverse query
<P, d, R> is evaluated by computing
(f.sub.p).sup.-1(d).andgate.R, where f.sub.p is the semantic
function associated to policy P.
[0010] The evaluation of a reverse query is in general much more
demanding, in terms of computing resources, in particular, time,
than evaluating a request against a policy. If the set of requests
of interest, R={r.sub.1, . . . , r.sub.n}, contains a relatively
small number of requests then the reverse query <P, d, R> may
be effectively evaluated by computing
f.sub.p(r.sub.1), . . . , f.sub.p(r.sub.n)
and picking only those requests which evaluate to d. That is, a
reverse query can be evaluated by sending each request of interest
to the PDP (loaded with the policy P) and then comparing the
returned decision with the expected decision d.
[0011] If the set R is large, however, the method described above
becomes impracticable, particularly in situations where the reverse
query needs to be evaluated in real-time, e.g., in the context of
an interactive system where a user would be waiting in real time
for the result of such evaluation.
SUMMARY OF THE INVENTION
[0012] It is in view of the above mentioned problems that the
present invention has been made.
[0013] A method for real-time evaluation of a reverse query to an
attribute-based access control policy, ABAC policy, (P) which is
enforced to control access to one or more resources in a computer
network, executes on a system comprising a processing means,
preferably a computer connected to a data network. In accordance
with a first aspect of the invention, the method comprises the
steps of:
[0014] i) receiving a reverse query indicating a given decision
(d), which is one of permit access and deny access, and a set (R)
of admissible access requests, each of which comprises one or more
attributes appearing in the ABAC policy and explicit values
assigned to these;
[0015] ii) extracting attributes to which all access requests in
the set (R) assign identical values;
[0016] iii) reducing the ABAC policy at least by substituting
values for the extracted attributes;
[0017] iv) caching the policy after said reducing as a simplified
policy (P');
[0018] v) translating the cached simplified policy (P') and the
given decision (d) into a satisfiable logic proposition in Boolean
variables (v.sub.i, i=1, 2, . . . );
[0019] vi) deriving all variable assignments
(c.sub.j=[v.sub.1=x.sub.j1, v.sub.2=x.sub.j2, . . . ], j=1, 2, . .
. ) satisfying the logic proposition; and
[0020] vii) extracting, based on the variable assignments thus
derived, all access requests from the set (R) for which the ABAC
policy (P) yields the given decision (d) (referred to below as
"valid requests").
[0021] The method alleviates the problems associated with the prior
art, since inter alia the reduction of the ABAC policy and the
caching of the intermediate result (simplified policy P') for later
use considerably reduces the computational load on the processing
means.
[0022] In a second aspect, the invention provides a system operable
to evaluate a reverse query, defining an expected decision, and a
subset of a set of admissible requests, over a policy in real time.
The system comprises a first storing means operable to store
policies. The system also comprises a partial request generation
means operable to construct a partial request from the subset of
the set of possible requests (cf. step ii). Furthermore, the system
also comprises a policy decision means connected to the partial
request generation means, and to the first storing means and
operable to partially evaluate the policy over the partial request,
resulting in a simplified policy (cf. steps iii, iv). The system
also comprises a translation means connected to the policy decision
means and operable to translate the simplified policy, the subset
of the set of possible requests, and the expected decision into a
propositional logic formula (cf. step v). Furthermore, the system
also comprises an analyzing means connected to the translation
means and operable to analyze the propositional logic formula in
order to determine a sequence of one or more conditions over
requests (cf. step vi). The conditions in the sequence are
sufficient in the sense that each corresponds to a variable
assignment that satisfies the logic proposition. The order of the
conditions in the sequence is not important. The system also
comprises a conversion means connected to the analyzing means, and
operable to convert the sequence of conditions to a set of valid
requests contained in the subset, and evaluate to the expected
decision (cf. step vii).
[0023] The main advantage with this system is that it can evaluate
a reverse query in real time. A further advantage with this system
is that it can make the evaluation of a reverse query in real time
even if the subset of requests contains a large number of
requests.
[0024] Step II in the method may be performed by (and corresponding
modules in the system may be adapted for) studying each of the
attributes appearing in the requests in the set (R) to discover
whether equal or different values are assigned to them. Attributes
with equal values in all requests are extracted. An attribute to
which some requests assign values and some do not is preferably not
extracted. Step II may be refined further by forming subsets within
the set (R), wherein a first group of attributes has identical
values in a first subset, a second group of attributes--possibly
overlapping with the first group--has identical values in a second
subset, and so forth. The reduction will then lead to a
corresponding number of simplified policies, so that the method
bifurcates into several branches, the results of which are gathered
to form the final result.
[0025] In step iv, the reduced policy is cached and forms a
simplified policy. Since the simplified policy can be represented
as a smaller set of processing instructions (code), it is in
general more economical to evaluate. As far as the XACML context is
concerned, it is noted that the simplified policy may be
represented in the same form as the original policy. However, the
simplified policy may in some cases require a richer representation
than standard XACML, possibly including a number of new quasi-error
states stemming from the fact that some attributes have not yet
been evaluated (substituted). For instance, a situation may arise
in which a rule cannot be evaluated for lack of target or lack of
values assumed by the attributes appearing in a condition in the
rule. The simplified policy may then contain an indication that the
rule is indeterminate, that is, temporarily s overriding the
standard evaluation rules, which may specify for this situation
that an evaluation error is to be signaled. This is useful since it
may turn out, when combining algorithms in the policy are applied,
that the sub-tree in which this rule is located is inconsequential
to the policy evaluation, so that this sub-tree may be eliminated
from the simplified policy. It is noted that if the simplified
policy is not represented in standard XACML, evaluation engines
adapted for standard XACML may need to be modified to evaluate a
simplified policy.
[0026] (The concept of a simplified policy and the technique of
partial evaluation have been described in more detail in the
applicant's earlier applications. Using the terminology of these
earlier applications, the initial request may be regarded as is a
partial request, and the step of reducing may be regarded as a
partial evaluation of the policy.)
[0027] Step iv may be further refined by evaluating attributes, for
which the values to be substituted are found using implicit
references defined by values given in a request together with the
structure of the policy. For instance, the nationality of a subject
may be retrievable from a database using the name of the subject as
a key.
[0028] Step vi may be performed by means of a SAT solver, i.e., a
functional entity implemented in hardware and/or software and
configured to input a satisfiable logic expression and to output,
in response thereto, a solution (or a variable assignment, or a set
of values of variables in the expression) for which the logic
expression evaluates to true. Many SAT solvers are known in the art
and available from commercial or non-commercial providers. The form
in which the logical expression is to be input may vary between
different SAT solvers, and this is preferably taken into account
when step v is implemented, so that compatibility can be ensured.
In general, an ABAC policy encoded in one of the customary or
standardized languages is not compatible. Some SAT solvers are
configured to return one solution even though the logic expression
may evaluate true for several variable assignments. It is desirable
in step vi to exhaust the set of solutions; this may be achieved
invoking the SAT solver repeated times, wherein a condition
excluding the previous solution is added to the logical expression
before a new repetition is initiated. As SAT solvers are typically
highly specialized for the task of finding a variable assignment
satisfying the expression, step vi can be completed very
efficiently.
[0029] Alternatively, step vi is carried out using techniques based
on the theory of binary decision diagrams (BDDs) and Reduced-Order
BDDs (ROBDDs), as outlined in B. Akers, "Binary Decision Diagrams",
IEEE Trans. Comp., vol. C-27, no. 6 (1978), p. 509 and R. E.
Bryant, "Graph-based algorithms for Boolean function manipulation",
IEEE Trans. Comp., vol. C-35, no. 8 (1986), p. 677. A plurality of
references in this area describe algorithms for translating a logic
expression into a BDD or ROBDD, and there exist further algorithms
for deriving exhaustive sets of solutions. These solutions may then
be converted back into a form that will allow those access requests
in the set (R) for which the policy yields the given decision to be
extracted. Implementations of such algorithms as libraries of
computer-executable code can be retrieved from commercial or
non-commercial sources. For example, the library JavaBDD can be
retrieved from http://sourceforge.net,
http://sourceforge.net/projects/javabdd,
http://javabdd.sourceforge.net/or archived versions of these pages.
A further BDD package is BuDDy, downloadable from
http://buddy.sourceforge.net. Compared with the SAT-solver approach
to carrying out step vi, the translation (step v) may require a
slightly greater effort if BDDs are used; step vi may on the other
hand execute more efficiently.
[0030] As the person skilled in computer science will realize when
studying this disclosure, there are further options for
implementing step vi. Since generally a faster evaluation happens
at the price of a more involved translation process, and
conversely, the selection of a particular implementation may depend
on facts related to the intended application or use, including the
complexity of the concerned ABAC policy and its degree of
nesting.
[0031] A further advantage in this context is achieved if the
system also comprises a policy information means which is connected
to the policy decision means, and the conversion means and is
operable to handle a set of attributes.
[0032] Furthermore, it is an advantage in this context if the
partial request generation means also is operable to examine the
subset of possible requests in order to determine (I) the set (D)
of attributes that are associated with exactly the same set of
values in all requests of the subset (R); (II) the set (A) of
attributes that are absent in all requests of the subset (R); and
(III) the set (U) of all other attributes not included in any of
the sets (D or A) of attributes.
[0033] A further advantage in this context is achieved if the
partial request generation means also is operable to, by using the
sets (D, A and U) of attributes, define the partial request which
(IV) associates to each attribute in the set (D) of attributes, the
exact set of values associated to it by any request in the subset
(R); (V) marks all attributes in the set (A) as not present; and
(VI) leaves all attributes in the set (U) undefined.
[0034] Furthermore, with particular reference to step v, it is an
advantage in this context if the translation means also is operable
to represent the simplified policy with a tree structure, and to,
whenever a sub-tree represents a Boolean expression that compares
an attribute with a fixed value, replace the whole sub-tree by a
variable.
[0035] A further advantage in the context of step v is achieved if
the translation is means also is operable to, from each condition
node and downwards, whenever a sub-tree represents a Boolean
expression, but at least one of its children evaluates to a
non-Boolean value, replace the whole sub-tree by a variable.
[0036] Furthermore, it is an advantage in the context of step v if
the system also comprises a second storing means connected to the
translation means, and to the conversion means, and operable to
store the correlation between each variable and the sub-tree it has
replaced.
[0037] A further advantage in the context of step v is achieved if
the variables can hold a value from the set, representing the
values true, false and indeterminate. This may be achieved by
substituting two associated Boolean variables for each such
variable capable of assuming three values. As such, (1,1) may
signify a true state, (0,0) may signify a false state, and (0,1)
may signify that the variable is indeterminate. Similarly, for a
tree (representing a policy or policy set) or sub-tree
(representing a subordinate policy or policy set), one may
substitute two associated Boolean values representing
(1,0)--permit, (0,0)--deny, (1,1)--indeterminate, (0,1)--not
applicable.
[0038] Furthermore, it is an advantage in this context if the
conversion means also is operable to, given a request r, determine
if it fulfills any condition, and if it does, then r is added to
the set R of valid requests.
[0039] The above mentioned problems are also solved with a method
for evaluating a reverse query, defining an expected decision, and
a subset (R) of a set of possible requests, over a policy (P) in
real-time. The method is performed with the aid of a system. The
method comprises the steps:
[0040] with the aid of a first storing means, comprised in the
system, to store policies;
[0041] with the aid of a partial request generation means,
comprised in the system, to construct a partial request from the
subset (R) of the set of possible requests;
[0042] with the aid of a policy decision means connected to the
partial request generation means, and to the first storing means,
to partially evaluate the policy over the partial request resulting
in a simplified policy;
[0043] with the aid of a translation means, connected to the policy
decision means, to translate the simplified policy, the subset of
the set of possible requests, is and the expected decision into a
propositional logic formula;
[0044] with the aid of an analyzing means connected to the
translation means, to analyze the propositional logic formula in
order to determine a sequence of conditions over requests; and
[0045] with the aid of a conversion means, connected to the
analyzing means, to convert the sequence of conditions to a set of
valid requests contained in the subset (R), and evaluate to the
expected decision.
[0046] The main advantage with this method is that it can evaluate
a reverse query in real-time. A further advantage with this method
is that it can make the evaluation of a reverse query in real-time
even if the subset of requests contains a large number of
requests.
[0047] A further advantage in this context is achieved if the
method also comprises the step:
[0048] with the aid of a policy information means, comprised in the
system, and connected to the policy decision means, and the
conversion means, to handle a set of attributes.
[0049] Furthermore, it is an advantage in this context if the
method also comprises the steps:
[0050] with the aid of the partial request generation means, to
examine the subset (R) of possible request in order to
determine
[0051] (I) the set (D) of attributes that are associated with
exactly the same set of values in all requests of the subset
(R);
[0052] (II) the set (A) of attributes that are absent in all
requests of the subset (R); and
[0053] (III) the set (U) of all other attributes not included in
any of the sets (D or A) of attributes.
[0054] A further advantage in this context is achieved if the
method also comprises the steps:
[0055] with the aid of the partial request generation means, by
using the sets (D, A and U) of attributes, to define the partial
request, which
[0056] (IV) associates to each attribute in the set (D) of
attributes, the exact set of values associated to it by any request
in the subset (R);
[0057] (V) marks all attributes in the set (A) as not present;
and
[0058] (VI) leaves all attributes in the set (U) undefined.
[0059] Furthermore, it is an advantage in this context if the
method also comprises the steps:
[0060] with the aid of the translation means, to represent the
simplified policy with a tree structure;
[0061] whenever a sub-tree represents a Boolean expression that
compares an attribute with a fixed value; and
[0062] to replace the whole sub-tree by a variable.
[0063] A further advantage in this context is achieved if the
method also comprises the step:
[0064] with the aid of the translation means, from each condition
node and downwards, whenever a sub-tree represents a Boolean
expression, but at least one of its children evaluates to a
non-Boolean value, to replace the whole sub-tree by a variable.
[0065] Furthermore, it is an advantage in this context if the
method also comprises the step:
[0066] with the aid of a second storing means, comprised in the
system, and connected to the translation means, to store a
correlation between each variable and the sub-tree it has
replaced.
[0067] A further advantage in this context is achieved if the
variables can hold a value from the set, representing the values
true, false and indeterminate.
[0068] Furthermore, it is an advantage in this context if the
method also comprises the steps:
[0069] with the aid of the conversion means, given a request
r.epsilon.R, to determine if it fulfills any condition; and
[0070] if it does, to add r to the set of valid requests.
[0071] The above mentioned problems are also solved with at least
one computer program product. The at least one computer program
product is/are directly loadable into the internal memory of at
least one digital computer, and comprises software code portions
for performing the steps of the method according to the present
invention when the at least one product is/are run on the at least
one computer.
[0072] The main advantage with this computer program product is
that it can evaluate a reverse query in real-time. A further
advantage with this product is that it can make the evaluation of a
reverse query in real-time even if the subset of requests contains
a large number of requests.
[0073] It will be noted that the term "comprises/comprising" as
used in this description is intended to denote the presence of a
given characteristic, step or component, without excluding the
presence of one or more other characteristics, features, integers,
steps, components or groups thereof.
BRIEF DESCRIPTION OF THE DRAWINGS
[0074] Embodiments of the invention will now be described with a
reference to the accompanying drawings, on which:
[0075] FIG. 1 is a block diagram of a system operable to evaluate a
reverse query, defining an expected decision, and a subset of a set
of possible requests, over a policy in real-time according to the
present invention;
[0076] FIG. 2 is a flow chart of a method for evaluating a reverse
query, defining an expected decision, and a subset of a set of
possible requests, over a policy in real-time according to the
present invention;
[0077] FIG. 3 schematically shows a number of computer program
products according to the present invention;
[0078] FIG. 4 illustrates an exemplifying AC policy architecture;
and
[0079] FIG. 5 is a tree representation of an ABAC policy set.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0080] In FIG. 1 there is disclosed a block diagram of a system 10
operable to evaluate a reverse query, defining an expected decision
(d), and a subset (R) of a s set of possible requests, over a
policy (P) in real-time according to the present invention. The
system 10 comprises a first storing means 12 operable to store
policies. Furthermore, the system 10 also comprises a partial
request generation means 14 operable to construct a partial request
(r.sub.partial) from the subset (R) of the set of possible
requests. As is apparent in FIG. 1, the system 10 also comprises a
policy decision means 16 connected to the partial request
generation means 14, and to the first storing means 12, and
operable to partially evaluate the policy (P) over the partial
request (r.sub.partial) resulting in a simplified policy (P').
Furthermore, the system 10 also comprises a translation means 20
connected to the policy decision means 16, and operable to
translate the simplified policy (P'), the subset (R) of the is set
of possible requests, and the expected decision (d) into a
propositional logic formula (F). The system 10 also comprises an
analyzing means 18 connected to the translation means 20, and
operable to analyze the propositional logic formula (F) in order to
determine a sequence [c.sub.1, . . . , c.sub.k] of conditions over
requests, preferably sufficient conditions. As also is apparent in
FIG. 1, the system 10 also comprises a conversion means 22
connected to the analyzing means 18, and operable to convert the
sequence [c.sub.1, . . . , c.sub.k] of conditions to a set of valid
requests contained in the subset (R), and evaluate to the expected
decision (d).
[0081] According to one alternative, the system 10 can also
comprise a policy information means 30 operable to handle a set of
attributes 32. The policy information means 30 is connected to the
policy decision means 16, and to the conversion means 22. These
connections are disclosed in FIG. 1 with broken lines, because
these elements are not mandatory in the system 10.
[0082] According to another alternative, the partial request
generation means 14 is also operable to examine the subset (R) of
the set of possible requests in order to determine (I) the set (D)
of attributes that are associated with exactly the same set of
values in all requests of the subset (R); (II) the set (A) of
attributes that are absent in all requests of the subset (R); and
(III) the set (U) of all other attributes not included in any of
the sets (D or A) of attributes.
[0083] According to a further alternative, the partial request
generation means 14 is also operable to, by using the sets (D, A
and U) of attributes, define the partial request (r.sub.partial)
which (IV) associates to each attribute in the set (D) of
attributes, the exact set of values associated to it by any request
in the subset (R); (V) marks all attributes in the set (A) as not
present; and (VI) leaves all attributes in the set (U)
undefined.
[0084] According to yet another alternative, the translation means
20 is also operable to represent the simplified policy (P') with a
tree structure, and to, whenever a sub-tree represents a Boolean
expression that compares an attribute with a fixed value, replace
the whole sub-tree by a variable (v.sub.i).
[0085] According to another alternative, the translation means 20
is also operable to, from each condition node and downwards,
whenever a sub-tree represents a Boolean expression, but at least
one of its children evaluates to a non-Boolean value, replace the
whole sub-tree by a variable (v.sub.i).
[0086] As also is apparent in FIG. 1, the system 10 can also
comprise a second storing means 24 operable to store the
correlation between each variable (v.sub.i) and the sub-tree it has
replaced. The second storing means 24 is connected to the
translation means 20, and to the conversion means 22. These
connections are disclosed in FIG. 1 with a broken line, because
these elements are not mandatory in the system 10.
[0087] Furthermore, according to another alternative, the variables
(v.sub.i) can hold a value from the set {T, F, .perp.},
representing the values true, false and indeterminate.
[0088] According to yet another alternative, the conversion means
22 is also operable to, given a request r.epsilon.R, determine if
it fulfills any condition c.sub.i, and if it does, then r is added
to the set of valid requests.
[0089] In FIG. 2 there is disclosed a flow chart of a method for
evaluating a reverse query, defining an expected decision (d), and
a subset (R) of a set of possible requests, over a policy (P) in
real-time according to the present invention. The method is
performed with the aid of a system 10 (see FIG. 1). The method
begins at block 50. The method continues, at block 52, with the
step: with the aid of a first storing means 12, comprised in the
system 10, to store policies. Thereafter, the method continues, at
block 54, with the step: with the aid of a partial request
generation means 14, comprised in the system 10, to construct a
partial request (r.sub.partial) from the subset (R) of the set of
possible requests. The method continues, at block 56, with the
step: with the aid of a policy decision means 16 connected to the
partial request generation means 14, to partially evaluate the
policy (P) over the partial request (r.sub.partial) resulting in a
simplified policy (P'). Thereafter, the method continues, at block
58, with the step: with the aid of a translation means 20,
connected to the policy decision means 16, to translate the
simplified policy (P'), the subset (R) of the set of possible
requests, and the expected decision (d) into a propositional logic
formula (F). The method continues, at block 60, with the step: with
the aid of an analyzing means 18 connected to the translation means
20, to analyze the propositional logic formula (F) in order to
determine a sequence [c.sub.i, . . . , c.sub.k] of conditions over
requests. Thereafter, the method continues, at block 62, with the
step: with the aid of a conversion means 22, connected to analyzing
means 18, to convert the sequence [c.sub.i, . . . , c.sub.k] of
conditions to a set of valid requests contained in the subset (R),
and evaluate to the expected decision (d). The is method is
completed at block 64.
[0090] According to one alternative, the method also comprises the
step: with the aid of a policy information means 30, comprised in
the system 10, and connected to the policy decision means 16, and
to the conversion means 22, to handle a set of attributes 32.
[0091] According to another alternative, the method also comprises
the steps: with the aid of the partial request generation means 14,
to examine the subset (R) of possible requests in order to
determine
[0092] (I) the set (D) of attributes that are associated with
exactly the same set of values in all requests of the subset
(R);
[0093] (II) the set (A) of attributes that are absent in all
requests of the subset (R); and
[0094] (III) the set (U) of all other attributes not included in
any of the sets (D or A) of attributes.
[0095] According to yet another alternative, the method also
comprises the steps: with the aid of the partial request generation
means 14, by using the sets (D, A and U) of attributes, to define
the partial request (r.sub.partial), which
[0096] (IV) associates to each attribute in the set (D) of
attributes, the exact set of values associated to it by any request
in the subset (R);
[0097] (V) marks all attributes in the set (A) as not present;
and
[0098] (VI) leaves all attributes in the set (U) undefined.
[0099] Furthermore, according to another alternative, the method
also comprises the steps:
[0100] with the aid of the translation means 20, to represent the
simplified policy (P') with a tree structure;
[0101] whenever a sub-tree represents a Boolean expression that
compares an attribute with a fixed value; and
[0102] to replace the whole sub-tree by a variable (v.sub.i).
[0103] According to a further alternative, the method also
comprises the step:
[0104] with the aid of the translation means 20, from each
condition node and downwards, whenever a sub-tree represents a
Boolean expression, but at least one of its children evaluates to a
non-Boolean value, to replace the whole sub-tree by a variable
(v.sub.i).
[0105] According to another alternative, the method also comprises
the step:
[0106] with the aid of a second storing means 24, comprised in the
system 10, and connected to the translation means 20, and to the
conversion means 22 to store a correlation between each variable
(v.sub.i) and the sub-tree it has replaced.
[0107] According to yet another alternative, the variables
(v.sub.i) can hold a value from the set {T, F, .perp.},
representing the values true, false and indeterminate.
[0108] Furthermore, according to another alternative, the method
also comprises the steps:
[0109] with the aid of the conversion means 22, given a request
r.epsilon.R, to determine if it fulfills any condition c.sub.i;
and
[0110] if it does, to add r to the set of valid requests.
[0111] The systems and methods disclosed hereinabove may be
implemented as software, firmware, hardware or a combination
thereof. In a hardware implementation, the division of tasks
between functional units referred to in the above description does
not necessarily correspond to the division into physical units; to
the contrary, one physical component may have multiple
functionalities, and one task may be carried out by several
physical components in cooperation. Certain components or all
components may be implemented as software executed by a digital
signal processor or microprocessor, or be implemented as hardware
or as an application-specific integrated circuit. Such software may
be distributed on computer readable media, which may comprise
computer storage media (or non-transitory media) and communication
media (or transitory media). As is well known to a person skilled
in the art, the term computer storage media includes both volatile
and nonvolatile, removable and non-removable media implemented in
any method or technology for storage of information such as
computer readable instructions, data structures, program modules or
other data. Computer storage media includes, but is not limited to,
RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM,
digital versatile disks (DVD) or other optical disk storage,
magnetic cassettes, magnetic tape, magnetic disk storage or other
magnetic storage devices, or any other medium which can be used to
store the desired information and which can be accessed by a
computer. Further, it is well known to the skilled person that
communication media typically embodies computer readable
instructions, data structures, program modules or other data in a
modulated data signal such as a carrier wave or other transport
mechanism and includes any information delivery is media.
[0112] In FIG. 3, some computer program products 302.sub.1, . . . ,
302.sub.n according to the present invention are schematically
shown. In FIG. 3, n different digital computers 300.sub.1, . . . ,
300.sub.n are shown, where n is an integer. In FIG. 3, n different
computer program products 302.sub.1, . . . , 302.sub.n are shown,
here shown in the form of floppy/compact discs. The different
computer program products 302.sub.1, . . . , 302.sub.n are directly
loadable into the internal memory of the n different computers
300.sub.1, . . . , 300.sub.n. Each computer program product
302.sub.1; . . . ; 302.sub.n comprises software code portions for
performing all the steps according to FIG. 2, when the
product/products 302.sub.1, . . . , 302.sub.n is/are run on the
computers 300.sub.1, . . . , 300.sub.n. The computer program
products 302.sub.1, . . . , 302.sub.n may, for instance, be in the
form of diskettes, RAM discs, magnetic tapes, magneto-optical discs
or some other suitable products.
[0113] FIG. 4 is a generalized block diagram of the XACML
architecture 100, although simplified, according to the prior art.
As stated before, XACML is an access control policy language. An
attempt to access a resource 102 is represented as a "Request",
which lists attributes of the subject 104, the resource 102, the
action and the environment 106. An attribute is an identifier, a
data type and a value. It can also be described as a variable with
a name (the identifier), a data type and a value. Most facts
relating to the subject 104, the resource 102, the action and the
environment 106 can be described in terms of attributes.
[0114] The request is constructed by a PEP 108. The purpose of a
PEP 108 is to guard access to a resource 102 and only let
authorized users through. The PEP 108 itself does not know who is
authorized, but it submits the request to a PDP 110, which contain
policies governing what requests are to be permitted or denied,
respectively. The PDP 110 evaluates the policies and returns a
permit/deny response to the PEP 108. The PEP 108 then either lets
the access proceed or stops it. As already noted, the PEP (Policy
Enforcement Point) may provide only some initial attribute values
and the PDP (Policy Decision Point) or other components may
dynamically fetch more values from remote sources as they are
needed. If all necessary values cannot be retrieved, the policy
evaluation may return an output to the effect that the policy is
indeterminate or not applicable in the circumstances, or an error
message.
[0115] A purpose of this architecture is to establish separation of
concerns, that is, to differentiate between policy decision making
and policy enforcement. Enforcement is by its nature specific to a
particular resource 102, while a decision engine can be made
general-purpose and reusable.
[0116] In general, policies can be nested to form a policy set, as
may be visualized in a tree form of the type shown in FIG. 2. The
combination of different policies is governed by combining
algorithms, which define what policy takes precedence over another
policy. The node "PolicySet 1" in FIG. 2 is of the "deny-overrides"
type, so that a "Deny" decision from one of the three sub-trees
will take precedence; hence, the "deny-overrides" operator acts as
logical AND. In contrast, decisions produced by sub-trees which
connect at a "permit-overrides" node are subject to logical OR.
[0117] At the lowest level of the tree shown in FIG. 2, there are
rules including effects (e.g., "Deny") and underlying conditions
formulated in terms of attributes, for instance,
"subject-nationality!=`US`", where "subject-nationality" is a
subject attribute and "US" is a constant. At several nodes above
the lowest level, there are conditions labelled "Target:", which
indicate the requests for which the sub-tree having its root at
that node is applicable. For example, if the condition
"document-stage=`draft`" evaluates to "false", then Policy 3,
including Rule 6, is not applicable and can be excluded from
evaluation.
FURTHER EMBODIMENTS
[0118] 1. A system (10) operable to evaluate a reverse query,
defining an expected decision (d), and a subset (R) of a set of
possible requests, over a policy (P) in real-time, said system (10)
comprising a first storing means (12) operable to store policies,
wherein said system (10) also comprises a partial request
generation s means (14) operable to construct a partial request
(r.sub.partial) from said subset (R) of said set of possible
requests, a policy decision means (16) connected to said partial
request generation means (14), and to the first storing means (12),
and operable to partially evaluate said policy (P) over said
partial request (r.sub.partial) resulting in a simplified policy
(P'), a translation means (20) connected to said policy decision
means (16), and operable to translate said simplified policy (P'),
said subset (R) of said set of possible requests, and said expected
decision (d) into a propositional logic formula (F), an analyzing
means (18) connected to said translation means (20), and operable
to analyze said propositional logic formula (F) in order to
determine a sequence [c.sub.i, . . . , c.sub.k] of conditions over
requests, and a conversion is means (22) connected to said
analyzing means (18), and operable to convert said sequence
[c.sub.i, . . . , c.sub.k] of conditions to a set of valid requests
contained in said subset (R), and evaluate to said expected
decision (d).
[0119] 2. A system (10) operable to evaluate a reverse query over a
policy (P) in real-time according to embodiment 1, wherein said
system (10) also comprises a policy information means (30)
connected to said policy decision means (16), and said conversion
means (22), and operable to handle a set of attributes (32).
[0120] 3. A system (10) operable to evaluate a reverse query over a
policy (P) in real-time according to embodiment 1 or 2, wherein
said partial request generation means (14) also is operable to
examine said subset (R) of possible requests in order to determine
(I) the set (D) of attributes that are associated with exactly the
same set of values in all requests of said subset (R); (II) the set
(A) of attributes that are absent in all requests of said subset
(R); and (III) the set (U) of all other attributes not included in
any of the sets (D or A) of attributes.
[0121] 4. A system (10) operable to evaluate a reverse query over a
policy (P) in real-time according to embodiment 3, wherein said
partial request generation means (14) also is operable to, by using
said sets (D, A and U) of attributes, define said partial request
(r.sub.partial) 1 which (IV) associates to each attribute in said
set (D) of attributes, the exact set of values associated to it by
any request in said subset (R); (V) marks all attributes in said
set (A) as not present; and (VI) leaves all attributes in said set
(U) undefined.
[0122] 5. A system (10) operable to evaluate a reverse query over a
policy (P) in real-time according to any one of embodiments 1-4,
wherein said translation means (20) also is operable to represent
said simplified policy (P') with a tree structure, and to, whenever
a sub-tree represents a Boolean expression that compares an
attribute with a fixed value, replace said whole sub-tree by a
variable (v.sub.i).
[0123] 6. A system (10) operable to evaluate a reverse query over a
policy (P) in real-time according to embodiment 5, wherein said
translation means (20) also is operable to, from each condition
node and downwards, whenever a sub-tree represents a Boolean
expression, but at least one of its children evaluates to a
non-Boolean value, replace said whole sub-tree by a variable
(v.sub.i).
[0124] 7. A system (10) operable to evaluate a reverse query over a
policy (P) in real-time according to embodiment 5, or 6, wherein
said system (10) also comprises a second storing means (24)
connected to said translation means (20), and to said conversion
means (22), and operable to store the correlation between each
variable (v.sub.i) and said sub-tree it has replaced.
[0125] 8. A system (10) operable to evaluate a reverse query over a
policy (P) in real-time according to embodiment 7, wherein said
variables (v.sub.i) can hold a value from the set {T, F, .perp.},
representing the values true, false and indeterminate.
[0126] 9. A system (10) operable to evaluate a reverse query over a
policy (P) in real-time according to any one of embodiments 5-8,
when dependent on embodiment 5, wherein said conversion means (22)
also is operable to, given a request r.epsilon.R, determine if it
fulfills any condition c.sub.i, and if it does, then r is added to
said set of valid requests.
[0127] 10. A method for evaluating, with the aid of a system (10),
a reverse query, defining an expected decision (d), and a subset
(R) of a set of possible requests, over a policy (P) in real-time,
said method comprises the steps:
[0128] with the aid of a first storing means (12), comprised in
said system (10), to store policies;
[0129] with the aid of a partial request generation means (14),
comprised in said system (10), to construct a partial request
(r.sub.partial) from said subset (R) of said set of possible
requests;
[0130] with the aid of a policy decision means (16) connected to
said partial request generation means (14), and to said first
storing means (12), to partially evaluate said policy (P) over said
partial request (r.sub.partial) resulting in a simplified policy
(P');
[0131] with the aid of a translation means (20), connected to said
policy decision means (16), to translate said simplified policy
(P'), said subset (R) of said set of possible requests, and said
expected decision (d) into a propositional logic formula (F);
[0132] with the aid of an analyzing means (18) connected to said
translation means (20), to analyze said propositional logic formula
(F) in order to determine a sequence [c.sub.i, . . . , c.sub.k] of
conditions over requests; and
[0133] with the aid of a conversion means (22), connected to said
analyzing means (18), to convert said sequence [c.sub.i, . . . ,
c.sub.k] of conditions to a set of valid requests contained in said
subset (R), and evaluate to said expected decision (d).
[0134] 11. A method for evaluating a reverse query over a policy
(P) in real-time according to embodiment 10, wherein said method
also comprises the step:
[0135] with the aid of a policy information means (30), comprised
in said system (10), and connected to said policy decision means
(16), and said conversion means (22), to handle a set of attributes
(32).
[0136] 12. A method for evaluating a reverse query over a policy
(P) in real-time according to embodiment 10 or 11, wherein said
method also comprises the steps:
[0137] with the aid of said partial request generation means (14),
to examine said subset (R) of possible requests in order to
determine
[0138] (I) the set (D) of attributes that are associated with
exactly the same set of values in all requests of said subset
(R);
[0139] (II) the set (A) of attributes that are absent in all
requests of said subset (R); and
[0140] (III) the set (U) of all other attributes not included in
any of the sets (D or A) of attributes.
[0141] 13. A method for evaluating a reverse query over a policy
(P) in real-time according to embodiment 12, wherein said method
also comprises the steps:
[0142] with the aid of said partial request generation means (14),
by using said sets (D, A and U) of attributes, to define said
partial request (r.sub.partial), which
[0143] (IV) associates to each attribute in said set (D) of
attributes, the exact set of values associated to it by any request
in said subset (R);
[0144] (V) marks all attributes in said set (A) as not present;
and
[0145] (VI) leaves all attributes in said set (U) undefined.
[0146] 14. A method for evaluating a reverse query over a policy
(P) in real-time according to any one of embodiments 10-13, wherein
said method also comprises is the steps:
[0147] with the aid of said translation means (20), to represent
said simplified policy (P') with a tree structure;
[0148] whenever a sub-tree represents a Boolean expression that
compares an attribute with a fixed value; and
[0149] to replace said whole sub-tree by a variable (v.sub.i).
[0150] 15. A method for evaluating a reverse query over a policy
(P) in real-time according to embodiment 14, wherein said method
also comprises the step:
[0151] with the aid of said translation means (20), from each
condition node and downwards, whenever a sub-tree represents a
Boolean expression, but at least one of its children evaluates to a
non-Boolean value, to replace said whole sub-tree by a variable
(v.sub.i).
[0152] 16. A method for evaluating a reverse query over a policy
(P) in real-time according to embodiment 14, or 15, wherein said
method also comprises the step:
[0153] with the aid of a second storing means (24), comprised in
said system (10), and connected to said translation means (20), and
to said conversion means (22), to store a correlation between each
variable (v.sub.i) and said sub-tree it has replaced.
[0154] 17. A method for evaluating a reverse query over a policy
(P) in real-time according to embodiment 16, wherein said variables
(v.sub.i) can hold a value from the set {T, F, .perp.},
representing the values true, false and indeterminate.
[0155] 18. A method for evaluating a reverse query over a policy
(P) in real-time according to any one of embodiments 14-17, when
dependent on embodiment 14, wherein said method also comprises the
steps:
[0156] with the aid of said conversion means (22), given a request
r.epsilon.R, to determine if it fulfills any condition c.sub.i;
and
[0157] if it does, to add r to said set of valid requests.
[0158] 19. At least one computer program product (102.sub.1, . . .
, 102.sub.n) directly loadable into the internal memory of at least
one digital computer (100.sub.1, . . . , 100.sub.n), comprising
software code portions for performing the steps of embodiment 10
when said is at least one product (102.sub.1, . . . , 102.sub.n)
is/are run on said at least one computer (100.sub.1, . . . ,
100.sub.n).
[0159] Further embodiments of the present invention will become
apparent to a person skilled in the art after studying the
description above. Even though the present description and drawings
disclose embodiments and examples, the invention is not restricted
to these specific examples. For instance, the invention can be
applied to control access to resources outside the context of
computing; as an example, access to the premises in a building can
be controlled if suitable identification means (e.g., card readers,
biometric sensors, which identify a person as a subject in a
guarding system) and actuators (e.g., electrically controllable
door locks) are provided and are communicatively connected to a
computer system for enforcing the AC policy. Numerous modifications
and variations can be made without departing from the scope of the
present invention, which is defined by the accompanying claims. Any
reference signs appearing in the claims are not to be understood as
limiting their scope.
* * * * *
References